Multiple attribute decision-making based on 3,4-quasirung fuzzy sets

Abstract

This paper extends the notion of Pythagorean fuzzy sets and Fermatean fuzzy sets to 3,4-quasirung fuzzy sets (3,. In 3,4-QFSs, the sum of the cube of the membership degree and fourth power of nonmembership degree is less than or equal to 1. Therefore, the 3,4-QFSs can express imprecise information more flexibly and elaborately due to its broader space. Here, we define the score function and accuracy function for the ranking of 3,4-QFSs. Also, we develop complementary functions and some operational rules for the 3,4-QFSs. Then, based on the defined operational rules, we propose 3,4-quasirung fuzzy weighted averaging (geometric), order weighed averaging (geometric), and hybrid averaging (geometric) aggregation operators. Next, we analyze some suitable properties of the presented operators. Moreover, we utilize the proposed 3,4-quasirung fuzzy weighted averaging (geometric) operators to develop a multiple attribute decisionmaking (MADM) model with 3,4-quasirung fuzzy data. The main advantage of 3,4-QFS is that it enables the decisionmakers to exploit additional spaces while applying to MADM problems. Finally, a numerical example concerning the selection of a learning management system is provided to check the validity of the proposed method. A comparative analysis with existing methods is given to verify the superiority of the proposed method.

Decision algorithm for picture fuzzy sets and Aczel Alsina aggregation operators based on unknown degree of wights

“…We also try to resolve some complicated challenges such as pattern recognition, structure development, green-supplied systems, similarity measures, medical diagnosis, and improvement in the construction sector. In the coming future, we will extend our developed research work in different fuzzy domains such as bipolar soft set [ 67 ], bipolar complex fuzzy set [ 68 ], complex spherical fuzzy set [ 69 ], 3,4-quasirung FSs [ 70 ], quasirung orthopair fuzzy sets [ 71 ], Z-fuzzy sets [ 72 ], Decomposed Fuzzy sets [ 73 ] and m-polar fuzzy sets [ 74 ], moreover, the proposed model can be integrated with different decision making models [ [75] , [76] , [77] ].…”

Decision algorithm for educational institute selection with spherical fuzzy heronian mean operators and Aczel-Alsina triangular norm

“…This effort is sure to motivate researchers and scholars to take their work in a new direction. Future work could expand the suggested methods to include linguistic data [ 65 ], bipolar complex fuzzy system [ 66 ], theory of linear diophantine fuzzy sets [ 67 ], quasirung orthopair fuzzy theory [ 68 ], 3, 4-quasirung fuzzy theory [ 69 ] and complex T-spherical fuzzy sets [ 70 ]. Moreover, the model can be integrated with the recent decision-making models [ [74] , [75] , [76] , [77] , [78] ].…”

Complex q-rung orthopair fuzzy Frank aggregation operators and their application to multi-attribute decision making

“…We have created a precedent to combine Frank aggregation operators with complex q-rung orthopair fuzzy set and make use of the complex q-rung orthopair fuzzy Frank aggregation operators to deal with decision-making problems. Since the method proposed in this paper cannot handle multi-attribute decision making in complex q-rung linguistic fuzzy environments or complex q-rung fuzzy N-soft environments, in future work, we will extend Frank aggregation operators under complex q-rung linguistic orthopair fuzzy environments, complex q-rung fuzzy N-soft environments and T‐spherical fuzzy environments, or develop Frank aggregation operators to 3, 4-quasirung fuzzy sets (Seikh and Mandal, 2022 ). In addition, we shall further generalize these defined operators to deal with Biogas plant implementation problem (Karmakar et al 2021 ), plastic ban problem (Seikh et al 2021a ), market share problem (Seikh et al 2021b ), social network analysis (Liu et al 2022a ), social trust propagation mechanism (Liu et al 2022b ) and incomplete probabilistic linguistic preference relations (Wang et al 2021 ; Liu et al 2020a , 2020b , 2020c ), or extend the aggregation operators to other domains, such as pattern recognition, cluster analysis and investment decisions.…”